Sub-mJy radio emission from high-redshift active galactic nuclei in the footprint of the VLA Sky Survey
Bibliographic record
Abstract
ABSTRACT Using empty-field ‘Quick Look’ images from the first two epochs of the VLA Sky Survey (VLASS) observations, centred on the positions of ∼3700 individually radio-non-detected active galactic nuclei (AGNs) at z ≥ 4, we performed image stacking analysis to examine the sub-mJy emission at 3 GHz. We found characteristic monochromatic radio powers of Pchar = (2–13) × 1024 W Hz−1, indicating that AGN-related radio emission is widespread in the sample. The signal-to-noise ratios of the redshift-binned median stacked maps are between 4–6, and we expect that with the inclusion of the yet to be completed third-epoch VLASS observations, the detection limit defined as signal-to-noise ratio SNR ≥ 6 could be reached, and the redshift dependence can be determined. To obtain information on the general spectral properties of the faint radio emission in high-redshift AGNs, we confined the sample to ∼3000 objects covered by both the VLASS and the Faint Images of the Radio Sky at Twenty-centimeters (FIRST) survey. We found that the flux densities from the median stacked maps show a characteristic spectral index of α* = −0.30 ± 0.15, which is in agreement with the median spectral index of the radio-detected z ≥ 4 AGNs from our high-redshift AGN catalogue. The three-band mid-infrared colour–colour diagram based on Wide-field Infrared Survey Explorer observations provides further support regarding the AGN contribution to the radio emission in the sub-mJy sample.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".